Well, sort of, at least.
For those of us who can’t get enough of English eccentrics, Brewer’s Rogues, Villains, Eccentrics by William Donaldson is probably the funniest book ever written. I mean, just to take one example, where else would you find an entry like this one?
Carlton, Sydney (1949- ), painter and decorator. Those who argue that bestiality should be treated with understanding had a setback in 1998 when Carlton, a married man from Bradford, was sentenced to a year in prison for having intercourse with a Staffordshire bull terrier, namned Badger. His defence was that Badger had made the first move. ‘I can’t help it if the dog took a liking to me,’ he told the court. This was not accepted.
As always for you, Jeanette Meyer.
Neoclassical economics nowadays usually assumes that agents that have to make choices under conditions of uncertainty behave according to Bayesian rules, axiomatized by Ramsey (1931) and Savage (1954) – that is, they maximize expected utility with respect to some subjective probability measure that is continually updated according to Bayes theorem. If not, they are supposed to be irrational, and ultimately – via some “Dutch book” or “money pump”argument – susceptible to being ruined by some clever “bookie”.
Bayesianism reduces questions of rationality to questions of internal consistency (coherence) of beliefs, but – even granted this questionable reductionism – do rational agents really have to be Bayesian? As I have been arguing elsewhere (e. g. here, here and here) there is no strong warrant for believing so.
In many of the situations that are relevant to economics one could argue that there is simply not enough of adequate and relevant information to ground beliefs of a probabilistic kind, and that in those situations it is not really possible, in any relevant way, to represent an individual’s beliefs in a single probability measure.
Say you have come to learn (based on own experience and tons of data) that the probability of you becoming unemployed in Sweden is 10 %. Having moved to another country (where you have no own experience and no data) you have no information on unemployment and a fortiori nothing to help you construct any probability estimate on. A Bayesian would, however, argue that you would have to assign probabilities to the mutually exclusive alternative outcomes and that these have to add up to 1, if you are rational. That is, in this case – and based on symmetry – a rational individual would have to assign probability 10% to becoming unemployed and 90% of becoming employed.
That feels intuitively wrong though, and I guess most people would agree. Bayesianism cannot distinguish between symmetry-based probabilities from information and symmetry-based probabilities from an absence of information. In these kinds of situations most of us would rather say that it is simply irrational to be a Bayesian and better instead to admit that we “simply do not know” or that we feel ambiguous and undecided. Arbitrary an ungrounded probability claims are more irrational than being undecided in face of genuine uncertainty, so if there is not sufficient information to ground a probability distribution it is better to acknowledge that simpliciter, rather than pretending to possess a certitude that we simply do not possess.
I think this critique of Bayesianism is in accordance with the views of John Maynard Keynes’ A Treatise on Probability (1921) and General Theory (1937). According to Keynes we live in a world permeated by unmeasurable uncertainty – not quantifiable stochastic risk – which often forces us to make decisions based on anything but rational expectations. Sometimes we “simply do not know.” Keynes would not have accepted the view of Bayesian economists, according to whom expectations “tend to be distributed, for the same information set, about the prediction of the theory.” Keynes, rather, thinks that we base our expectations on the confidence or “weight” we put on different events and alternatives. To Keynes expectations are a question of weighing probabilities by “degrees of belief”, beliefs that have preciously little to do with the kind of stochastic probabilistic calculations made by the rational agents modeled by Bayesian economists.
Stressing the importance of Keynes’ view on uncertainty John Kay writes in Financial Times:
Keynes believed that the financial and business environment was characterised by “radical uncertainty”. The only reasonable response to the question “what will interest rates be in 20 years’ time?” is “we simply do not know” …
For Keynes, probability was about believability, not frequency. He denied that our thinking could be described by a probability distribution over all possible future events, a statistical distribution that could be teased out by shrewd questioning – or discovered by presenting a menu of trading opportunities. In the 1920s he became engaged in an intellectual battle on this issue, in which the leading protagonists on one side were Keynes and the Chicago economist Frank Knight, opposed by a Cambridge philosopher, Frank Ramsey, and later by Jimmie Savage, another Chicagoan.
Keynes and Knight lost that debate, and Ramsey and Savage won, and the probabilistic approach has maintained academic primacy ever since. A principal reason was Ramsey’s demonstration that anyone who did not follow his precepts – anyone who did not act on the basis of a subjective assessment of probabilities of future events – would be “Dutch booked” … A Dutch book is a set of choices such that a seemingly attractive selection from it is certain to lose money for the person who makes the selection.
I used to tell students who queried the premise of “rational” behaviour in financial markets – where rational means are based on Bayesian subjective probabilities – that people had to behave in this way because if they did not, people would devise schemes that made money at their expense. I now believe that observation is correct but does not have the implication I sought. People do not behave in line with this theory, with the result that others in financial markets do devise schemes that make money at their expense.
Although this on the whole gives a succinct and correct picture of Keynes’s view on probability, I think it’s necessary to somewhat qualify in what way and to what extent Keynes “lost” the debate with the Bayesians Frank Ramsey and Jim Savage.
In economics it’s an indubitable fact that few mainstream neoclassical economists work within the Keynesian paradigm. All more or less subscribe to some variant of Bayesianism. And some even say that Keynes acknowledged he was wrong when presented with Ramsey’s theory. This is a view that has unfortunately also been promulgated by Robert Skidelsky in his otherwise masterly biography of Keynes. But I think it’s fundamentally wrong. Let me elaborate on this point (the argumentation is more fully presented in my book John Maynard Keynes (SNS, 2007)).
It’s a debated issue in newer research on Keynes if he, as some researchers maintain, fundamentally changed his view on probability after the critique levelled against his A Treatise on Probability by Frank Ramsey. It has been exceedingly difficult to present evidence for this being the case.
Ramsey’s critique was mainly that the kind of probability relations that Keynes was speaking of in Treatise actually didn’t exist and that Ramsey’s own procedure (betting) made it much easier to find out the “degrees of belief” people were having. I question this both from a descriptive and a normative point of view.
What Keynes is saying in his response to Ramsey is only that Ramsey “is right” in that people’s “degrees of belief” basically emanates in human nature rather than in formal logic.
Patrick Maher, former professor of philosophy at the University of Illinois, even suggests that Ramsey’s critique of Keynes’s probability theory in some regards is invalid:
Keynes’s book was sharply criticized by Ramsey. In a passage that continues to be quoted approvingly, Ramsey wrote:
“But let us now return to a more fundamental criticism of Mr. Keynes’ views, which is the obvious one that there really do not seem to be any such things as the probability relations he describes. He supposes that, at any rate in certain cases, they can be perceived; but speaking for myself I feel confident that this is not true. I do not perceive them, and if I am to be persuaded that they exist it must be by argument; moreover, I shrewdly suspect that others do not perceive them either, because they are able to come to so very little agreement as to which of them relates any two given propositions.” (Ramsey 1926, 161)
I agree with Keynes that inductive probabilities exist and we sometimes know their values. The passage I have just quoted from Ramsey suggests the following argument against the existence of inductive probabilities. (Here P is a premise and C is the conclusion.)
P: People are able to come to very little agreement about inductive proba- bilities.
C: Inductive probabilities do not exist.
P is vague (what counts as “very little agreement”?) but its truth is still questionable. Ramsey himself acknowledged that “about some particular cases there is agreement” (28) … In any case, whether complicated or not, there is more agreement about inductive probabilities than P suggests.
“If … we take the simplest possible pairs of propositions such as “This is red” and “That is blue” or “This is red” and “That is red,” whose logical relations should surely be easiest to see, no one, I think, pretends to be sure what is the probability relation which connects them.” (162)
I agree that nobody would pretend to be sure of a numeric value for these probabilities, but there are inequalities that most people on reflection would agree with. For example, the probability of “This is red” given “That is red” is greater than the probability of “This is red” given “That is blue.” This illustrates the point that inductive probabilities often lack numeric values. It doesn’t show disagreement; it rather shows agreement, since nobody pretends to know numeric values here and practically everyone will agree on the inequalities.
“Or, perhaps, they may claim to see the relation but they will not be able to say anything about it with certainty, to state if it ismore or less than 1/3, or so on. They may, of course, say that it is incomparable with any numerical relation, but a relation about which so little can be truly said will be of little scientific use and it will be hard to convince a sceptic of its existence.” (162)
Although the probabilities that Ramsey is discussing lack numeric values, they are not “incomparable with any numerical relation.” Since there are more than three different colors, the a priori probability of “This is red” must be less than 1/3 and so its probability given “This is blue” must likewise be less than 1/3. In any case, the “scientific use” of something is not relevant to whether it exists. And the question is not whether it is “hard to convince a sceptic of its existence” but whether the sceptic has any good argument to support his position …
Ramsey concluded the paragraph I have been quoting as follows:
“Besides this view is really rather paradoxical; for any believer in induction must admit that between “This is red” as conclusion and “This is round” together with a billion propositions of the form “a is round and red” as evidence, there is a finite probability relation; and it is hard to suppose that as we accumulate instances there is suddenly a point, say after 233 instances, at which the probability relation becomes finite and so comparable with some numerical relations.” (162)
Ramsey is here attacking the view that the probability of “This is red” given “This is round” cannot be compared with any number, but Keynes didn’t say that and it isn’t my view either. The probability of “This is red” given only “This is round” is the same as the a priori probability of “This is red” and hence less than 1/3. Given the additional billion propositions that Ramsey mentions, the probability of “This is red” is high (greater than 1/2, for example) but it still lacks a precise numeric value. Thus the probability is always both comparable with some numbers and lacking a precise numeric value; there is no paradox here.
I have been evaluating Ramsey’s apparent argument from P to C. So far I have been arguing that P is false and responding to Ramsey’s objections to unmeasurable probabilities. Now I want to note that the argument is also invalid. Even if P were true, it could be that inductive probabilities exist in the (few) cases that people generally agree about. It could also be that the disagreement is due to some people misapplying the concept of inductive probability in cases where inductive probabilities do exist. Hence it is possible for P to be true and C false …
I conclude that Ramsey gave no good reason to doubt that inductive probabilities exist.
Ramsey’s critique made Keynes more strongly emphasize the individuals’ own views as the basis for probability calculations, and less stress that their beliefs were rational. But Keynes’s theory doesn’t stand or fall with his view on the basis for our “degrees of belief” as logical. The core of his theory – when and how we are able to measure and compare different probabilities – he doesn’t change. Unlike Ramsey he wasn’t at all sure that probabilities always were one-dimensional, measurable, quantifiable or even comparable entities.
Neoliberal privatization — what a great idea …
“The distinction between wage and profit-led growth is a major feature of neo-Kaleckian
growth theory. The essence of the distinction is that in a wage-led economy an increase
in the wage share (i.e. a decrease in the profit share) increases economic activity and
growth, whereas in a profit-led economy it has the reverse effects. This distinction has
important implications for policy, especially in the current environment of stagnation and high unemployment. If economies are wage-led, it suggests policy that increases the
wage share is a powerful means of raising growth and lowering unemployment. The
converse holds for economies that are profit-led …
These policy implications have triggered an extensive econometric literature that
aims to identify whether economies and economic regions are wage or profit-led. The
implicit fundamental assumption within that empirical literature is an economy’s or an
economic region’s character (i.e. whether it is wage or profit-led) is exogenously
determined by deep primitive parameters. The current paper questions that assumption
and explores the foundations of what determines whether an economy is wage or profitled …
The theoretical analysis gives rise to a Post-Keynesian analogue of the Lucas critique (Lucas, 1976). Lucas argued that the estimated econometric impact of policy was endogenous and depended on agents’ expectations of policy. In like vein, the current paper shows that whether an economy is wage or profit-led will depend on existing policies. Consequently, it is not possible to classify an economy as being intrinsically wage or profit-led. Instead, the econometrically identified character of the economy is contingent on policy and may change with changes in policy.
At the policy level, the paper shows that the growth–inequality trade-off posed by profit-led economies can be finessed by changing the distribution of the wage share. Consequently, it may be possible to have faster growth and less inequality in economies that appear profit-led. Even more significantly, if the wage distribution is changed sufficiently, the economy can flip from being profit-led to being wage-led.“
Inspired by the work of Doctors Without Borders (Médecins Sans Frontières), I have recently started a project called Economists Without Borders (Economistes Sans Frontières). Its purpose is to inoculate the global economy against the virus of neoliberalism. Last week, I had two difficult “missions” to Vienna and Warsaw.
In Vienna, I confronted an outbreak of the neoliberal globalization – free trade strain of the virus. Without doubt, this is the most virulent and dangerous of all strains. People who get infected become blind to all evidence, deaf to all argument and prone to intellectual condescension. Massachusetts Avenue in Washington DC is a hot zone of infection. The bad news is that if you are over forty and infected it is doubtful you can be cured. However, younger patients have a chance of recovery. Here is the anti-viral I prescribed titled “The Theory of Global Imbalances: Mainstream Economics vs. Structural Keynesianism”.
In Warsaw, I confronted an outbreak of Milton Friedmanism which is one of the oldest strains of neoliberal virus. Friedmanism is a gateway virus that weakens defenses against other neoliberal strains and younger minds are particularly susceptible to it. The good news is that if diagnosed early there is a good chance of recovery. However, if treatment is delayed, intellectual ossification and closed-mindedness sets in. This ossification is almost always associated with inflation obsessive compulsive disorder and austerity fever. Here is the treatment I recommend titled “Milton Friedman’s Economics and Political Economy: An Old Keynesian Critique”.
- Karl Marx, Das Kapital (1867)
- Thorstein Veblen, The Theory of the Leisure Class (1899)
- Joseph Schumpeter, The Theory of Economic Development (1911)
- Nikolai Kondratiev, The Major Economic Cycles (1925)
- Gunnar Myrdal, The Political Element in the Development of Economic Theory (1930)
- John Maynard Keynes, The General Theory (1936)
- Paul Sweezy, Theory of Capitalist Development (1956)
- Joan Robinson, Accumulation of Capital (1956)
- John Kenneth Galbraith, The Affluent Society (1958)
- Piero Sraffa, Production of Commodities by Means of Commodities (1960)
- Johan Åkerman, Theory of Industrialism (1961)
- Axel Leijonhufvud, Keynes and the Classics (1969)
- Nicholas Georgescu-Roegen, The Entropy Law and the Economic Process (1971)
- Michal Kalecki, Selected Essays on the Dynamics of the Capitalist Economy (1971)
- Paul Davidson, Money and the Real World (1972)
- Hyman Minsky, John Maynard Keynes (1975)
- Philip Mirowski, More Heat than Light (1989)
- Tony Lawson, Economics and Reality (1997)
- Steve Keen, Debunking Economics (2001)
- John Quiggin, Zombie Economics (2010)
The desire in the profession to make universalistic claims following certain standard procedures of statistical inference is simply too strong to embrace procedures which explicitly rely on the use of vernacular knowledge for model closure in a contingent manner. More broadly, such a desire has played a vital role in the decisive victory of mathematical formalization over conventionally verbal based economic discourses as the proncipal medium of rhetoric, owing to its internal consistency, reducibility, generality, and apparent objectivity. It does not matter that [as Einstein wrote] ‘as far as the laws of mathematics refer to reality, they are not certain.’ What matters is that these laws are ‘certain’ when ‘they do not refer to reality.’ Most of what is evaluated as core research in the academic domain has little direct bearing on concrete social events in the real world anyway.